The Role Of Artificial Intelligence In Enhancing Blockchain Security

Topic Information

Dear Colleagues,

Blockchain technology, which allows untrusted individuals to connect with others in a verifiable manner, has attracted much attention from both academia and industry. It is now used commercially for various applications such as tracking ownership, digital assets and voting rights. Blockchain is transforming our daily lives in every aspect, including banks and other financial institutions, hospitals, companies, and governments, among others. To make a blockchain application smart, Artificial Intelligence (AI) is being widely studied, which can build smart machines capable of performing tasks that typically require human intelligence, such as the ability to reason or to learn from past experience. For instance, AI algorithms can help blockchain applications handle data more efficiently without human intervention. The intelligence provided by AI can also benefit the design of smart contract in blockchains. Now it is possible to create deep learning neural networks, which can perform quickly and accurately for real-world blockchain applications.

The use of blockchain can provide various merits, such as transparency, data integrity, and enhanced security. By combining AI with blockchain, there is potential to make a real-world system more secure, intelligent, and efficient. For instance, blockchain can be used to ensure the integrity of shared data or models that would be used by AI, including deep learning and many machine learning techniques. The blockchain-empowered AI system is believed to be more robust against adversarial attacks. However, such a combination is not mature at the current stage, and many challenges remain unsolved, which are highlighted as follows: (1) Blockchain suffers many performance limitations, i.e., when the nodes or transactions become large, its efficiency is significantly degraded. (2) Both blockchain- and AI-based systems may leak private information, especially when the system aggregates data from various nodes. (3) Blockchain and AI systems are the main targets for cyber attackers, and various attacks have been posed on these systems, such as the 51% attack, double spending attacks, etc. Hence, how to combine blockchain with AI in a secure and intelligent way needs more research efforts.

This Topic focuses on using blockchain and AI to secure applications, software, data and systems. We invite original research, practice and surveys that investigate securing applications with blockchain and artificial intelligence. The topics of interest include, but are not limited to:

  • Machine learning for privacy preservation and system security
  • Data security and privacy on blockchain
  • Artificial intelligence models for blockchain systems
  • AI-empowered secure blockchain applications
  • AI-empowered blockchain in forensics
  • Blockchain and AI for intrusion detection
  • Digital preservation with AI and blockchain
  • AI-driven smart contracts
  • Secure computing on AI-empowered blockchain
  • AI-driven secure applications, data, software and systems
  • Availability, recovery and auditing with blockchain and AI
  • Trust management with blockchain and AI
  • Privacy protection with blockchain and AI
  • Blockchain and AI-secured systems
  • Secure applications supported by information theory or entropy
  • Blockchain or AI systems by applying information theory or entropy

Prof. Dr. Zheng YanDr. Xiaokang ZhouDr. Weizhi MengTopic Editors

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC entropy 2.7 4.7 1999 20.8 Days CHF 2600 futureinternet 3.4 6.7 2009 11.8 Days CHF 1600 algorithms 2.3 3.7 2008 15 Days CHF 1600 information 3.1 5.8 2010 18 Days CHF 1600 make 3.9 8.5 2019 19.9 Days CHF 1800 Preprints is a platform dedicated to making early versions of research outputs permanently available and citable. MDPI journals allow posting on preprint servers such as Preprints.org prior to publication. For more details about reprints, please visit https://www.preprints.org.

Published Papers (4 papers)

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